class_docstr: AlexNet model from the `"One weird trick..." <https://arxiv.org/abs/1404.5997>`_ paper.
  
  Parameters
  ----------
  classes : int, default 1000
      Number of classes for the output layer.
code: def __init__(self, classes=1000, **kwargs):
      super(AlexNet, self).__init__(**kwargs)
      self.features = nn.HybridSequential()
      self.features.add(
          nn.Conv2D(
              64,
              kernel_size=11,
              strides=4,
              padding=2,
              activation="relu",
          )
      )
      self.features.add(nn.MaxPool2D(pool_size=3, strides=2))
      self.features.add(
          nn.Conv2D(192, kernel_size=5, padding=2, activation="relu")
      )
      self.features.add(nn.MaxPool2D(pool_size=3, strides=2))
      self.features.add(
          nn.Conv2D(384, kernel_size=3, padding=1, activation="relu")
      )
      self.features.add(
          nn.Conv2D(256, kernel_size=3, padding=1, activation="relu")
      )
      self.features.add(
          nn.Conv2D(256, kernel_size=3, padding=1, activation="relu")
      )
      self.features.add(nn.MaxPool2D(pool_size=3, strides=2))
      self.features.add(nn.Flatten())
      self.features.add(nn.Dense(4096, activation="relu"))
      self.features.add(nn.Dropout(0.5))
      self.features.add(nn.Dense(4096, activation="relu"))
      self.features.add(nn.Dropout(0.5))
  
      self.output = nn.Dense(classes)
  
file_path: mxnet/python/mxnet/gluon/model_zoo/vision/alexnet.py
imports: import os
  from ....device import cpu
  from ...block import HybridBlock
  from ...None import nn
  from ....None import base
  from ....util import use_np, wrap_ctx_to_device_func
label_desc: Use image node_id 1 to create a new AlexNet object from inherited base classes: HybridBlock with example: obj = AlexNet(classes)